Efficient-Computing
Explore methods developed by Huawei Noah's Ark Lab for efficient computing, emphasizing data-efficient model compression and binary networks. The repository includes advancements in pruning (e.g., GAN-pruning), model quantization (e.g., DynamicQuant), and self-supervised learning (e.g., FastMIM). Discover training acceleration techniques and efficient object detection methods like Gold-YOLO. Also, find efficient solutions for low-level vision tasks with models such as IPG. These resources are designed to optimize neural network performance, focusing on minimal training data use.
